scholarly journals Beyond the hockey stick: Climate lessons from the Common Era

2021 ◽  
Vol 118 (39) ◽  
pp. e2112797118 ◽  
Author(s):  
Michael E. Mann
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Model ◽  
Focal Point ◽  
Ice Cores ◽  
Climate History ◽  
Hockey Stick ◽  
The Common ◽  
Climate Model Simulations ◽  
Common Era

More than two decades ago, my coauthors, Raymond Bradley and Malcolm Hughes, and I published the now iconic “hockey stick” curve. It was a simple graph, derived from large-scale networks of diverse climate proxy (“multiproxy”) data such as tree rings, ice cores, corals, and lake sediments, that captured the unprecedented nature of the warming taking place today. It became a focal point in the debate over human-caused climate change and what to do about it. Yet, the apparent simplicity of the hockey stick curve betrays the dynamicism and complexity of the climate history of past centuries and how it can inform our understanding of human-caused climate change and its impacts. In this article, I discuss the lessons we can learn from studying paleoclimate records and climate model simulations of the “Common Era,” the period of the past two millennia during which the “signal” of human-caused warming has risen dramatically from the background of natural variability.

scholarly journals Constraining the temperature history of the past millennium using early instrumental observations

2012 ◽  
Vol 8 (3) ◽  
pp. 1653-1685 ◽  
Author(s):  
P. Brohan ◽  
R. Allan ◽  
E. Freeman ◽  
D. Wheeler ◽  
C. Wilkinson ◽  
...  
Keyword(s):  
Temperature Change ◽  
Large Scale ◽  
Climate Model ◽  
Ice Cores ◽  
East India Company ◽  
Temperature History ◽  
British Library ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
Proxy Reconstructions

Abstract. The current assessment that twentieth-century global temperature change is unusual in the context of the last thousand years relies on estimates of temperature changes from natural proxies (tree-rings, ice-cores etc.) and climate model simulations. Confidence in such estimates is limited by difficulties in calibrating the proxies and systematic differences between proxy reconstructions and model simulations. As the difference between the estimates extends into the relatively recent period of the early nineteenth century it is possible to compare them with a reliable instrumental estimate of the temperature change over that period, provided that enough early thermometer observations, covering a wide enough expanse of the world, can be collected. One organisation which systematically made observations and collected the results was the English East-India Company (EEIC), and their archives have been preserved in the British Library. Inspection of those archives revealed 900 log-books of EEIC ships containing daily instrumental measurements of temperature and pressure, and subjective estimates of wind speed and direction, from voyages across the Atlantic and Indian Oceans between 1789 and 1834. Those records have been extracted and digitised, providing 273 000 new weather records offering an unprecedentedly detailed view of the weather and climate of the late eighteenth and early nineteenth centuries. The new thermometer observations demonstrate that the large-scale temperature response to the Tambora eruption and the 1809 eruption was modest (perhaps 0.5 °C). This provides a powerful out-of-sample validation for the proxy reconstructions – supporting their use for longer-term climate reconstructions. However, some of the climate model simulations in the CMIP5 ensemble show much larger volcanic effects than this – such simulations are unlikely to be accurate in this respect.

scholarly journals Constraining the temperature history of the past millennium using early instrumental observations

2012 ◽  
Vol 8 (5) ◽  
pp. 1551-1563 ◽  
Author(s):  
P. Brohan ◽  
R. Allan ◽  
E. Freeman ◽  
D. Wheeler ◽  
C. Wilkinson ◽  
...  
Keyword(s):  
Temperature Change ◽  
Large Scale ◽  
Climate Model ◽  
Ice Cores ◽  
East India Company ◽  
Temperature History ◽  
British Library ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
Proxy Reconstructions

Abstract. The current assessment that twentieth-century global temperature change is unusual in the context of the last thousand years relies on estimates of temperature changes from natural proxies (tree-rings, ice-cores, etc.) and climate model simulations. Confidence in such estimates is limited by difficulties in calibrating the proxies and systematic differences between proxy reconstructions and model simulations. As the difference between the estimates extends into the relatively recent period of the early nineteenth century it is possible to compare them with a reliable instrumental estimate of the temperature change over that period, provided that enough early thermometer observations, covering a wide enough expanse of the world, can be collected. One organisation which systematically made observations and collected the results was the English East India Company (EEIC), and their archives have been preserved in the British Library. Inspection of those archives revealed 900 log-books of EEIC ships containing daily instrumental measurements of temperature and pressure, and subjective estimates of wind speed and direction, from voyages across the Atlantic and Indian Oceans between 1789 and 1834. Those records have been extracted and digitised, providing 273 000 new weather records offering an unprecedentedly detailed view of the weather and climate of the late eighteenth and early nineteenth centuries. The new thermometer observations demonstrate that the large-scale temperature response to the Tambora eruption and the 1809 eruption was modest (perhaps 0.5 °C). This provides an out-of-sample validation for the proxy reconstructions – supporting their use for longer-term climate reconstructions. However, some of the climate model simulations in the CMIP5 ensemble show much larger volcanic effects than this – such simulations are unlikely to be accurate in this respect.

Common EOFs in atmospheric science and large-scale flow

2021 ◽  
Author(s):  
Abdel Hannachi ◽  
Kathrin Finke ◽  
Nickolay Trendafilov
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Sequential Algorithm ◽  
Atmospheric Variability ◽  
Orthogonal Function ◽  
Conventional Analysis ◽  
The Common ◽  
Climate Model Simulations ◽  
Large Scale Flow

<p>Conventional analysis of the large-scale atmospheric variability and teleconnections are obtained using the empirical orthogonal function (EOF) method, which was developed mainly to deal with single fields. With the increase of the amount of observed/simulated large-scale atmospheric data including climate models, e.g., CMIP, there is a need to develop methods with efficient algorithms that enable analysis and comparison/validation of climate model simulations. Here we describe the common EOF method, which finds common patterns of a set of large scale atmospheric fields, and enables comparing several model outputs simultaneously. A step-wise/sequential algorithm is presented, which avoids the difficulty encountered in previous algorithms related to the lack of simultaneous monotonic change of the eigenvalues of all fields. The theory and algorithm are presented, and the application to large-scale teleconnections from various reanalysis products and CMIP6 are discussed.</p>

scholarly journals Comparison and assessment of large-scale surface temperature in climate model simulations

2019 ◽  
Vol 5 (1) ◽  
pp. 67-85
Author(s):  
Raquel Barata ◽  
Raquel Prado ◽  
Bruno Sansó
Keyword(s):  
Surface Temperature ◽  
Seasonal Changes ◽  
Large Scale ◽  
Climate Model ◽  
Internal Variability ◽  
Temperature Variability ◽  
Data Driven ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. We present a data-driven approach to assess and compare the behavior of large-scale spatial averages of surface temperature in climate model simulations and in observational products. We rely on univariate and multivariate dynamic linear model (DLM) techniques to estimate both long-term and seasonal changes in temperature. The residuals from the DLM analyses capture the internal variability of the climate system and exhibit complex temporal autocorrelation structure. To characterize this internal variability, we explore the structure of these residuals using univariate and multivariate autoregressive (AR) models. As a proof of concept that can easily be extended to other climate models, we apply our approach to one particular climate model (MIROC5). Our results illustrate model versus data differences in both long-term and seasonal changes in temperature. Despite differences in the underlying factors contributing to variability, the different types of simulation yield very similar spectral estimates of internal temperature variability. In general, we find that there is no evidence that the MIROC5 model systematically underestimates the amplitude of observed surface temperature variability on multi-decadal timescales – a finding that has considerable relevance regarding efforts to identify anthropogenic “fingerprints” in observational surface temperature data. Our methodology and results present a novel approach to obtaining data-driven estimates of climate variability for purposes of model evaluation.

scholarly journals The Iso2k Database: A global compilation of paleo-δ<sup>18</sup>O and δ<sup>2</sup>H records to aid understanding of Common Era climate

2020 ◽  
Author(s):  
Bronwen L. Konecky ◽  
Nicholas P. McKay ◽  
Olga V. Churakova (Sidorova) ◽  
Laia Comas-Bru ◽  
Emilie P. Dassié ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Global Environmental Change ◽  
Global Scale ◽  
Proxy Records ◽  
Global Environmental ◽  
Past 2000 Years ◽  
Wide Range ◽  
Terrestrial Sediments ◽  
Common Era

Abstract. Reconstructions of global hydroclimate during the Common Era (CE; the past ~ 2000 years) are important for providing context for current and future global environmental change. Stable isotope ratios in water are quantitative indicators of hydroclimate on regional to global scales, and these signals are encoded in a wide range of natural geologic archives. Here we present the Iso2k database, a global compilation of previously published datasets from a variety of natural archives that record the stable oxygen (δ18O) or hydrogen (δ2H) isotopic composition of environmental waters, which reflect hydroclimate changes over the CE. The Iso2k database contains 756 isotope records from the terrestrial and marine realms, including: glacier and ground ice (205); speleothems (68); corals, sclerosponges, and mollusks (145); wood (81); lake sediments and other terrestrial sediments (e.g., loess) (158); and marine sediments (99). Individual datasets have temporal resolutions ranging from sub-annual to centennial, and include chronological data where available. A fundamental feature of the database is its comprehensive metadata, which will assist both experts and non-experts in the interpretation of each record and in data synthesis. Key metadata fields have standardized vocabularies to facilitate comparisons across diverse archives and with climate model simulated fields. This is the first global-scale collection of water isotope proxy records from multiple types of geological and biological archives. It is suitable for evaluating hydroclimate processes through time and space using large-scale synthesis, model-data intercomparison and (paleo)data assimilation. The Iso2k database is available for download at: https://doi.org/10.6084/m9.figshare.11553162 (McKay and Konecky, 2020).

scholarly journals Regional Climate Model Emulator based on Deep Learning: Concept and First Evaluation of a Novel Hybrid Downscaling Approach

2021 ◽  
Author(s):  
Antoine Doury ◽  
Samuel Somot ◽  
Sébastien Gadat ◽  
Aurélien Ribes ◽  
Lola Corre
Keyword(s):  
Climate Change ◽  
Network Architecture ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate ◽  
Near Surface ◽  
The Way

Abstract Providing reliable information on climate change at local scale remains a challenge of first importance for impact studies and policymakers. Here, we propose a novel hybrid downscaling method combining the strengths of both empirical statistical downscaling methods and Regional Climate Models (RCMs). The aim of this tool is to enlarge the size of high-resolution RCM simulation ensembles at low cost.We build a statistical RCM-emulator by estimating the downscaling function included in the RCM. This framework allows us to learn the relationship between large-scale predictors and a local surface variable of interest over the RCM domain in present and future climate. Furthermore, the emulator relies on a neural network architecture, which grants computational efficiency. The RCM-emulator developed in this study is trained to produce daily maps of the near-surface temperature at the RCM resolution (12km). The emulator demonstrates an excellent ability to reproduce the complex spatial structure and daily variability simulated by the RCM and in particular the way the RCM refines locally the low-resolution climate patterns. Training in future climate appears to be a key feature of our emulator. Moreover, there is a huge computational benefit in running the emulator rather than the RCM, since training the emulator takes about 2 hours on GPU, and the prediction is nearly instantaneous. However, further work is needed to improve the way the RCM-emulator reproduces some of the temperature extremes, the intensity of climate change, and to extend the proposed methodology to different regions, GCMs, RCMs, and variables of interest.

scholarly journals Space-based geoengineering: Challenges and requirements

2009 ◽  
Vol 224 (3) ◽  
pp. 571-580 ◽  
Author(s):  
C R McInnes
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Large Scale ◽  
Climate Model ◽  
Carbon Dioxide Concentration ◽  
Complex Solution ◽  
Lagrange Point ◽  
Simple Climate Model ◽  
Earth’S Climate

The prospect of engineering the Earth's climate (geoengineering) raises a multitude of issues associated with climatology, engineering on macroscopic scales, and indeed the ethics of such ventures. Depending on personal views, such large-scale engineering is either an obvious necessity for the deep future, or yet another example of human conceit. In this article a simple climate model will be used to estimate requirements for engineering the Earth's climate, principally using space-based geoengineering. Active cooling of the climate to mitigate anthropogenic climate change due to a doubling of the carbon dioxide concentration in the Earth's atmosphere is considered. This representative scenario will allow the scale of the engineering challenge to be determined. It will be argued that simple occulting discs at the interior Lagrange point may represent a less complex solution than concepts for highly engineered refracting discs proposed recently. While engineering on macroscopic scales can appear formidable, emerging capabilities may allow such ventures to be seriously considered in the long term. This article is not an exhaustive review of geoengineering, but aims to provide a foretaste of the future opportunities, challenges, and requirements for space-based geoengineering ventures.

scholarly journals Evaluation of the updated regional climate model RACMO2.3: summer snowfall impact on the Greenland Ice Sheet

2015 ◽  
Vol 9 (5) ◽  
pp. 1831-1844 ◽  
Author(s):  
B. Noël ◽  
W. J. van de Berg ◽  
E. van Meijgaard ◽  
P. Kuipers Munneke ◽  
R. S. W. van de Wal ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Elevation Gradient ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Ice Cores ◽  
Detailed Comparison ◽  
Ablation Zone ◽  
Surface Mass

Abstract. We discuss Greenland Ice Sheet (GrIS) surface mass balance (SMB) differences between the updated polar version of the RACMO climate model (RACMO2.3) and the previous version (RACMO2.1). Among other revisions, the updated model includes an adjusted rainfall-to-snowfall conversion that produces exclusively snowfall under freezing conditions; this especially favours snowfall in summer. Summer snowfall in the ablation zone of the GrIS has a pronounced effect on melt rates, affecting modelled GrIS SMB in two ways. By covering relatively dark ice with highly reflective fresh snow, these summer snowfalls have the potential to locally reduce melt rates in the ablation zone of the GrIS through the snow-albedo-melt feedback. At larger scales, SMB changes are driven by differences in orographic precipitation following a shift in large-scale circulation, in combination with enhanced moisture to precipitation conversion for warm to moderately cold conditions. A detailed comparison of model output with observations from automatic weather stations, ice cores and ablation stakes shows that the model update generally improves the simulated SMB-elevation gradient as well as the representation of the surface energy balance, although significant biases remain.

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